One-dimensional Approach Research Articles

A numerical framework for modeling evaporation and combustion of isolated, spherically-symmetric, multi-component fuel droplets

This paper presents a comprehensive numerical framework for simulating the evaporation and combustion of isolated, spherically-symmetric, multi-component fuel droplets. The framework incorporates a detailed description of chemical reactions in the gaseous phase and is capable of modeling pure evaporation, autoignition, and hot-wire ignition scenarios.The transport equations for mass, species, and energy are solved in both the liquid (droplet) and gaseous (surrounding atmosphere) phases. Diffusion in the liquid phase is described using the Stefan–Maxwell theory, while in the gaseous phase, both molecular and thermal diffusion are considered. The model also includes the thermophoretic effect for carbonaceous particles and accounts for gas radiation through various models, ranging from optically-thin approximations to more complex methods like the P1 and discrete ordinate methods. Non-gray radiative effects are handled using the Weighted-Sum-of-Gray-Gases Model (WSGGM). Liquid/gas interface conditions are evaluated by imposing flux continuity of mass and energy, along with thermodynamic equilibrium for species. Deviations from ideal thermodynamic behavior in the liquid droplet are managed by incorporating a suitable activity coefficient or by using a proper cubic equation of state. Additionally, the presence of supporting fibers is modeled using a simplified one-dimensional approach. The transport equations are solved using the method of lines, with spatial discretization performed via the finite difference method on a body-fitted grid. The resulting system of Differential–Algebraic Equations (DAEs) is then solved using a fully-coupled approach.Thanks to its generality in terms of kinetic and thermodynamic descriptions and the reduced computational time, the proposed framework offers significant potential for advancing our understanding of the complex combustion processes of multi-component liquid fuels and for enhancing the planning and execution of experiments involving isolated fuel droplets.

Comprehensive two-dimensional analytical modeling of groundwater levels in bi-directional sloping heterogeneous aquifers under variable recharge conditions

This paper develops a comprehensive two-dimensional (2D) groundwater model that surpasses traditional one-dimensional approaches by incorporating extensive hydrological and geological data typically acquired through well drilling. The primary objective of this research is to explore and characterize the complex dynamics of groundwater flow within sloping heterogeneous aquifers subject to rainfall-induced recharge events. To achieve this, the study utilizes the 2D Boussinesq equation, which is enhanced with meticulously defined boundary conditions to more accurately reflect real-world scenarios. The Integral Transform Technique (ITT) is employed to derive an analytical solution that integrates the effects of variable rainfall recharge, aquifer inclination angles, and inherent heterogeneity. This analytical model effectively captures varying recharge dynamics, both spatially and temporally, contributing to a better understanding and management of groundwater systems. The paper presents a new analytical framework, offering deeper insights into how natural factors impact porous medium behavior, thereby providing strategic references for sustainable water resource management.

How to measure and manage country reputation

Countries benefit from a good reputation in terms of gaining a higher foreign direct investment inflow, a growing export volume, becoming more attractive as tourist destinations and, last but not least, by improving their populations’ well-being. Consequently, many countries endeavor to manage their public perception actively. Since communication influences perception, advertising plays a particularly important role in the latter. However, countries need to fathom which opinions they need to encourage in order to ensure others’ optimal perceptions of them. A prerequisite for tackling this challenge is a model that measures and explains country reputation. This study develops such a model. Our model conceptualizes reputation as a two-dimensional attitudinal construct, thereby avoiding one-dimensional approaches’ shortcomings. It refers to the cognition-related dimension as competence, whereas the affect-related dimension is termed likability. It measures reputation, as perceived by stakeholders, by means of six reflective indicators. Furthermore, the model employs a catalogue of 30 formative indicators — structured by means of five key constructs — to identify the drivers of country reputation. By cultivating impactful drivers, countries are able to apply targeted measures to alter their reputations’ ratings on the two dimensions (i.e. competence and likability). We employed data from Germany, the United States, and the United Kingdom to develop our model. Relevant criteria highlight the model’s reliability and validity. A benchmark analysis of the proposed model compared to that of existing approaches illustrates its superiority in terms of its convergent and criterion validity.

Mathematical modeling of an isothermal tubular bioreactor coupled with batch culture for ethanol production: a one-dimensional approach

Mathematical modeling of an isothermal tubular bioreactor coupled with batch culture for ethanol production: a one-dimensional approach

Influence of social cleavage and media usage on political behavior: a case of Pakistan

Increasingly media provides ample opportunities for the audiences to make media choices and form different levels of exposure along political lines. Predominately, Pakistan’s media is recognized as an irreplaceable tool in sparking change in the political landscape, forgoing national-regional identities, and bridging social gaps. Due to recent technological advancements citizens’ media usage brought changes in the political behavior of citizens regarding party choices and voting behavior. Such changes in the political behavior of citizens affect decision making which is influenced by social cleavage of education, gender, and age. However, contrary to similar historical changes, these advances have widened rather than narrowed societal cleavages. The objective of the paper is to explore the influence of social cleavage and media usage on political behavior of students and faculty in Pakistan specifically NUML university, Islamabad. This research explores how social cleavage and recent advances in digital media access changed the political behavior of faculty and students of NUML university. The paper employed survey-based research with a sample of 250 faculty members and students of NUML, Islamabad. According to results, it is concluded that social cleavage of education, age, and gender plays a vital role in transforming the political behavior of both faculty members and students. Likewise, persistent use of social media portrays positive political participation along with accountable voting behavior, whereby males are more active in participating in political activities as compared to females. The paper has policy implications for a one-dimensional media approach for ignoring solutions to political problems and understanding citizenship rights. Focused and well-defined policies are required to bring youth back to broadcasting media.

Two-inlet lagoon systems: Interaction between basins and effects on tidal prisms

In a lagoon basin, the tidal prism is related to the section of its inlet by a simple monomial relationship [L. J. LeConte, “Discussion on the paper, ‘notes on the improvement of river and harbor outlets in the United States,’ by D. A. Watt.” Trans. ASCE 55, 306–308 (1905); M. P. O'Brien, “Estuary tidal prism related to entrance areas,” Civil Eng. 1(8), 738–739 (1931); and J. T. Jarrett, Tidal Prism - Inlet Area Relationships (Coastal Engineering Research Center, US Army Corps of Engineers, Fort Belvoir, VA, 1976)]. Although it is not dimensionally correct and there are sophisticated models in two or three dimensions, this relationship is widely used because of its simplicity. Having a simple relationship can be very important, especially when it is necessary to make quick, albeit approximate, evaluations. To maintain this simplicity, the same monomial relationship is often used in multi-inlet lagoons, even if the initial assumptions are not fully met. Another difficulty in applying a monomial relationship to a multi-inlet lagoon is the definition of the area of each basin. In this paper, we propose a simple Eulerian, hydrodynamic, one-dimensional approach based on the dynamic response of a nonlinear harmonic system and a harmonic analysis of the interaction between two basins in a lagoon system. With such an approach, the definition of the basin surface is overcome simply by working on topographic control basins. The study leads to the definition of a relatively simple relationship for the estimation of tidal prisms, while maintaining the flexibility of a monomial relationship. If the geometrical characteristics and the bottom friction of the inlet channel, the topographic surface of the basins and the amplitude of the tide in the open sea are known, this relationship can be used to estimate the tidal prism in individual basins. The application of this relationship to two-dimensional numerical cases and real multi-inlet lagoons shows good agreement with experimental data.

Investigation of the Filling of a Spherical Pore Body with a Nonwetting Fluid: A Modeling Approach and Computational Fluid Dynamics analysis

AbstractUnderstanding the dynamics of the filling process of a pore body with a nonwetting fluid is important in the context of dynamic pore network models and others. It can justify many of the assumptions behind the different rules that describe how the network behaves during imbibition and drainage processes. It also provides insight into the different regimes pertinent to this system. The filling process starts with the contact line pinning at the pore entrance. Three regimes can be identified during the filling process that is related to how the contact line advances. In the first two regimes, the contact line pins at the pore entrance while the emerging droplet develops, and in the third one, the contact line departs the entrance of the pore and advances along the pore surface. During the first regime, which is brief, the curvature of the meniscus increases, and likewise, the corresponding capillary pressure, while in the other two regimes, the curvature decreases and so does the capillary pressure. Such behavior results in the rate at which the nonwetting fluid invades the pore to change. It initially decreases, then increases as the meniscus advances. The radius of curvature of the meniscus, eventually, increases to infinity for which the interface assumes a flat configuration. A one-dimensional modeling approach is developed that accounts for all these regimes. The model also considers the two immiscible fluids over a wide spectrum of contrast in viscosity. Information about the mean velocity of the invading fluid, the location of the contact line, the radius of curvature of the meniscus, the volume of the emerging droplet, and several others are among the details that the model provides. A computational fluid dynamics (CFD) simulation has also been considered to confirm the proposed fates of the interface and to provide a framework for comparisons. The results of the validation process show, generally, a very good match between the model and the CFD analysis.

Research on identification, classification, and policy development for urban shrinkage: A case study of Liaoning Province, China

Under the influence of economic globalization and the transformation of pillar industries, cities are facing phenomena such as slow economic growth and population outflow, which indicate urban shrinkage. However, the theoretical framework for this phenomenon remains incomplete, and measurement standards are inconsistent. Therefore, studying urban shrinkage is of significant importance. This paper analyzes the current status and causes of urban shrinkage in Liaoning Province, China, and proposes an accurate model for identifying shrinkage. It utilizes a two-step diagnostic method that incorporates both one-dimensional and multidimensional approaches to identify shrinking cities and applies systematic clustering methods to categorize urban population changes. By observing and analyzing the population and economic data of 30 cities over 12 years, this study assesses urban shrinkage from the perspectives of population change and multivariate indicators. It identifies five cities with significant shrinkage, categorized into mild, moderate, and severe levels. Based on multiple linear regression and grey relational analysis, the study examines the impact of socio-economic factors on population changes and offers corresponding development suggestions.

Fractional-Order Interval Parameter State Space Model of the One-Dimensional Heat Transfer Process

In this paper, the new non-integer-order state space model of heat processes in a one-dimensional metallic rod is addressed. The fractional orders of derivatives along space and time are not exactly known, and they are described by intervals. The proposed model is the interval expanding of the state space fractional model of heat conduction and dissipation in a one-dimensional metallic rod. It is expected to better describe reality because the interval order of each real process is difficult to estimate. Using intervals enables describing the uncertainty. The presented interval model can be applied to the modeling of many real thermal processes in the industry and building. For example, it can describe the thermal conductivity of building walls. The one-dimensional approach can be applied because only the direction from inside to outside is important, and the heat distribution along the remaining directions is uniform. The paper describes the basic properties of the proposed model and supports the theory via simulations in MATLAB R2020b and experiments executed with the use of a real experimental laboratory system equipped with miniature temperature sensors and supervised by PLC and SCADA systems. The main results from the paper point out that the uncertainty of both fractional orders impacts the crucial properties of the model. The uncertainty of the derivative along the time affects only the dynamics, but the disturbance of the derivative along the length disturbs both the static and dynamic properties of the model.

Dimensional effects in analysis of laser-induced-desorption diagnostics data

The accurate assessment of the local tritium concentration in the tokamak first wall by means of the laser-induced desorption (LID) diagnostics is sought as one the key solutions to monitoring the local radioactive tritium content in the first wall of the fusion reactor ITER. Numerical models of gas desorption from solids used for LID simulation are usually closed with the one-dimensional transport models. In this study, the temperature and particle dynamics in the target irradiated by a short laser pulse during LID are analyzed by means of the two-dimensional model to assess the validity of using one-dimensional approximation for recovering the diagnostics signal. The quantitative estimates for the parameters governing the heat and particle transfer are presented. The analytical expressions for the sample spatiotemporal temperature profiles driven by the target irradiation with a Gaussian laser beam with the trapezoid temporal shape are derived. The obtained relations are used to simulate tritium desorption from a tungsten sample driven by pulsed heating. It is shown that depending on the ratio between the laser spot radius and the heat diffusion length, the one-dimensional approach can noticeably overestimate the sample temperature in the limit of small laser spot radius (estimated for tungsten as ∼0.5–1.0 mm), resulting in more than 100% larger amounts of tritium desorbed from the target, compared to the two-dimensional approximation. In the limit of large laser spot radius (≥1.5 mm), both approaches yield comparable amounts of tritium desorbed from the sample.

Promoting precision surface irrigation through hydrodynamic modelling and microtopographic survey

Precision irrigation aims to deliver water and nutrients to crops at exactly the right time, in the right place and in the right amount. While surface irrigation is often perceived as less precise, accurate water distribution, wise use of resources and high efficiency can still be achieved with careful land preparation, astute irrigation management and rigorous performance monitoring. In this study, we advocate the innovative concept of Precision Surface Irrigation, centered around three key design and operational principles that are: well-organized field geometry (and microtopography), precise control of hydraulic-hydrological variables and, finally, regular performance evaluation. These pillars are then integrated into a simulation environment capable of capturing the intricacies of surface irrigation dynamics. Conducted in northern Italy's Padana plain, the study contrasts one-dimensional (WinSRFR) and two-dimensional (IrriSurf2D) irrigation dynamic modeling. Data collection includes boundary geometries, inflow rates, intervention durations, and microtopography, facilitating spatial performance assessment from both the models. The results show that the versatility of the two-dimensional modelling approach was able to reproduce well the observed water depths and the phases of water advance and depletion both in time and space within the studied border irrigation strips, even in complex situations where the strips were hydraulically connected. The RMSE between observed and simulated maximum water depth and waterfront advance time was less than 2.1 cm and 1.9 min, respectively. The two-dimensional approach was also able to detect the cross variability of irrigation dynamics, and to provide a spatial assessment of irrigation performance at high resolution. In conclusion, while the one-dimensional hydrodynamic approach to describing the hydraulic behavior of surface irrigation and field-scale irrigation performance remains valid, the two-dimensional approach provides, in our case study and reasonably elsewhere, a valid simulation environment for spatially characterizing irrigation dynamics in the context of Precision Surface Irrigation.

From grape to wine: A thorough compound specific isotopic, enantiomeric and quali-quantitative investigation by means of gas chromatographic analysis

In this study, multiple analytical approaches, including simultaneous enantiomeric and isotopic analysis, were employed to thoroughly investigate the volatile fraction in Moscato giallo grape berries and wines. For the qualitative and quantitative profiling, a fast GC-QqQ/MS approach was successfully utilized. However, prior to isotopic analysis, the extracts underwent an additional concentration step, necessitating an assessment of isotopic fractionation during the concentration process. Once the absence of carbon isotopic fractionation was confirmed, this research aimed to develop a suitable gas chromatographic method for the simultaneous detection of both enantiomeric and isotopic ratios of target monoterpenoids in Moscato giallo samples. To address the limitations associated with a one-dimensional approach, multidimensional gas chromatography was employed to enhance separation before IRMS and qMS detections. Utilizing a Deans switch transfer device, the coupling of an apolar column in the first dimension and a chiral cyclodextrin-based stationary phase in the second dimension proved effective for this purpose. The data obtained from the analysis of Moscato giallo samples allowed for the assessment of natural isotopic and enantiomeric distributions in grapes and wines for the first time in the literature. Significant enantiomeric excesses were observed for the target terpenoids investigated. Regarding isotopic distribution, a consistent trend was observed for all detected target terpenols, including the linalool enantiomers. To date, this study represents the first investigation of simultaneous δ13C and chiral investigation of the main terpenoids in oenological products in the literature.

Susceptibility versus flexural stiffness in the stability of hybrid laminate columns with a rectangular cross section for a 1D model

Hybrid columns of FGM/FML type with inhomogeneous transverse structure perpendicular to their length are discussed. After that, laminated columns with different layups of laminate plies are discussed, with focus put on the effect exerted by many coupling of the stiffness submatrix on the lowest eigenvalue load. All columns were simply supported The study uses three methods for determining the lowest eigenvalues. The first two are analytical beam methods (i.e. 1D modelling approaches) based on the use of the Euler-Bernoulli theory. The proposed 1D methods are a generalisation of the well-known approach of determining the lowest eigenloads of isotropic columns. The first approach is to solve the eigenproblem directly from the differential equation of the deflection line. The second approach assumes that the curvature of the beam depends on the susceptibility of the beam. This is a fundamental assumption in the bending theory of beams and thin plates. The third method is the FEM (3D shell approach) which is used for the verification of the previous calculations. A comparison of the obtained results showed that the proposed 1D (one-dimensional) approach based on the full susceptibility matrix, which is the inverse stiffness matrix was as accurate as the 3D (three-dimensional) FEM shell model. The relative difference does not exceed 3%. Second 1D approach based on the stiffness matrix yields many times unacceptable differences relative to the reference results obtained by the FEM method. This comparison clearly demonstrates that an approach based on the assumption that curvature is directly proportional to susceptibility in flexural composite structures produces accurate results for all types of coupling.The existing literature extensively explores the impacts of stiffness matrix elements on both the linear and non-linear stability of laminate columns. However, there is a notable absence of studies focusing on the influence of susceptibility. This crucial aspect has been overlooked in prior studies. The present paper endeavors to fill this gap by shedding light on the influence of susceptibility, thereby emphasizing its significance in the analysis of laminate column stability.

Frequent Pattern Associative Rules in Multiple Dimensions

This paper explores frequent pattern mining in multidimensional data and its extension beyond traditional one-dimensional approaches. While association rule mining is widely used in market basket analysis, its application to multidimensional datasets presents new challenges due to the increased complexity and sparsity of the data. This research reviews existing multidimensional mining techniques, focusing on frequent pattern associative rules, and evaluates their performance. Several real-world applications, such as business intelligence, healthcare analytics, and sensor networks, are discussed. The paper also proposes a framework for efficient pattern discovery and suggests areas for future research

A one-dimensional convolutional neural network-based deep learning approach for predicting cardiovascular diseases

Early detection of cardiovascular diseases (CVDs) is crucial for managing cardiovascular diseases and improving patient outcomes. Deep neural networks have the potential to reduce the reliance on costly and time-consuming clinical tests, leading to cost savings for patients and healthcare systems. This study proposes the development of specialized convolutional neural networks for the automated selection of essential variables, employing various preprocessing procedures. It evaluates the approach using the UCI repository heart disease dataset, focusing on early-stage heart disease identification to enhance early prediction and intervention for CVD. To address the challenge of achieving higher accuracy, we introduce an approach using one-dimensional convolutional neural networks, incorporating extensive testing to optimize the network architecture and enhance predictive performance. Additionally, recognizing the impact of features on accuracy, a comprehensive data analysis was performed. Through a meticulous selection process, we identified and utilized key features that significantly influenced the accuracy of our model, contributing to more reliable predictions. Finally, cross-validation techniques were implemented to precisely evaluate the efficacy of our work. Numerous experiments were conducted to demonstrate the relevance of our research. The prediction accuracy was found to be 99.95% when employing a train–test approach, while it was approximately 98.53% when employing K-Fold cross-validation. In comparison to existing literature, our approach outperforms a recent best study that proposed a Catboost model, achieving an F1-score of about 92.3% and an average accuracy of 90.94%. This signifies a substantial improvement in predictive performance, with a percentage improvement of approximately 9.90% compared to the Catboost model.

Non-Invasive Prediction of Choledocholithiasis Using 1D Convolutional Neural Networks and Clinical Data.

This paper introduces a novel one-dimensional convolutional neural network that utilizes clinical data to accurately detect choledocholithiasis, where gallstones obstruct the common bile duct. Swift and precise detection of this condition is critical to preventing severe complications, such as biliary colic, jaundice, and pancreatitis. This cutting-edge model was rigorously compared with other machine learning methods commonly used in similar problems, such as logistic regression, linear discriminant analysis, and a state-of-the-art random forest, using a dataset derived from endoscopic retrograde cholangiopancreatography scans performed at Olive View-University of California, Los Angeles Medical Center. The one-dimensional convolutional neural network model demonstrated exceptional performance, achieving 90.77% accuracy and 92.86% specificity, with an area under the curve of 0.9270. While the paper acknowledges potential areas for improvement, it emphasizes the effectiveness of the one-dimensional convolutional neural network architecture. The results suggest that this one-dimensional convolutional neural network approach could serve as a plausible alternative to endoscopic retrograde cholangiopancreatography, considering its disadvantages, such as the need for specialized equipment and skilled personnel and the risk of postoperative complications. The potential of the one-dimensional convolutional neural network model to significantly advance the clinical diagnosis of this gallstone-related condition is notable, offering a less invasive, potentially safer, and more accessible alternative.

Effects of rotational speed on transient cooling performance of nozzle spray with liquid nitrogen in a rotor-stator cavity

This paper presents the results of an experimental investigation into the cooling performance of a rotor-stator cavity with liquid nitrogen spraying. The experiments were conducted under varying rotational Reynolds numbers ranging from 1.70 × 106 to 5.12 × 106. The effects of rotational speed on temperature drop rate are studied and compared in detail, as well as the heat transfer coefficient distribution. Sufficient data, such as heat flux, injection rate, and injection pressure, were collected to provide a basis for further study in explaining the spray and evaporation over the cavity. It was found that the cooling performance of the rotating disc is strongly affected by the rotational speed. The short-term period exhibits a peak cooling rate of 14°C/s, in contrast to the sustained cooling rate during the spray process at rotational speeds of 500r/min, which amounts to 0.9°C/s. The occurrence of cavitation and evaporation within the nozzle results in a reduction of flow coefficient and fluctuation of the injection differential pressure. The transient cooling performance is well-explained by the temperature changes and cooling-down time under different rotational speeds. The analysis of the heat transfer coefficient is further enhanced through an evaluation of the convective and conductive heat transfer rates using a one-dimensional theoretical approach. The average temperature of the disc is expected to decrease by 100°C within a time frame no longer than 120 s. Additionally, after a duration of 120 s, the average heat transfer rate on the cold side is anticipated to surpass 8000 W/(m·K).

Numerical investigation of phase change material integration in structured thermocline systems for concentrated solar power

The integration of encapsulated PCM in a structured thermal energy storage system is studied. The fluid and filler material are discretized using a one-dimensional approach, while the PCM is discretized two-dimensionally. The accumulated energy for the height percentage of PCM and cutoff temperature differences are obtained for three PCMs, NaNO3, KOH and H380, to obtain the best options to enhance the accumulated energy using encapsulated PCM.

Influence of PCMs on thermal performance of wet fire protective clothing

The inclusion of phase change materials (PCMs) in firefighting protective clothing (FPC) has been previously shown to be beneficial during the exposure stage, but detrimental in the post-exposure, mainly due to PCM latent heat release towards the skin, after the exposure. It is unclear whether that is also the case for when the FPC is wet. Hence, in this study, a one-dimensional numerical approach is used to study the effect of PCM parameters (PCM mass, melting temperature) and global heat flux, on the thermal performance of a wet fire protective clothing. It is concluded that under wet conditions, the PCM amount, and its phase change temperature have a significant effect on thermal performance, depending on the heat exposure scenario considered. Great benefits are observed in introducing PCMs to prevent water condensation near the skin, but at the cost of greater PCM re-solidification skin damage.

Application of The Homotopy Perturbation Method to the Neutron Diffusion Equation

The Homotopy Perturbation Method (HPM) has been shown to be effective in solving both linear and nonlinear differential equations in mathematics, making it useful in a wide range of applications in the fields of physics and engineering. In this study, the Homotopy Perturbation Method was applied to the neutron diffusion equation for a one-dimensional time-independent approach. The Laplace operator of the neutron diffusion equation was considered for Cartesian, spherical and cylindrical coordinates. The critical radius values obtained for three different systems were calculated for all possible values of the relevant material parameter B. The results show that the solution of the neutron diffusion equation is agree with the literature.